Design, implement and own production features and services that support agentic AI behavior
Develop backend systems, APIs, and data integrations that support agentic workflows as scale
Add logging, metrics, and tracing to ensure systems are observable and debuggable in production
Collaborate with product, design, and platform teams to translate workflows and requirements into technical solutions
Participate actively in code reviews, design discussions, and security reviews
Requirements
1+ years professional software engineering experience, with strong proficiency in Python or a similar backend language
Experience designing and operating production services or distributed systems
Hands on experience using LLMs or generative AI APIs in real applications
Solid understanding of agentic AI patterns, including tool use, task decomposition, planning, and feedback loops
Experience integrating with REST APIs, databases, queues, and third party services
Experience with observability and evaluation of AI systems (logging, tracing, offline or online evaluation)
Ability to reason about scalability, latency, reliability, and cost trade offs
Clear written and verbal communication skills, with attention to detail
Bachelor's degree in computer science, engineering, or related field
Experience using agentic AI or orchestration frameworks (such as LangChain/LangGraph, CrewAI, and more)
Familiarity with cloud infrastructure, containerization, and CI/CD pipelines
Demonstrated ability to learn and apply emerging AI tools and patterns quickly
Exposure to ArcGIS Enterprise, ArcGIS Online or other geospatial technologies
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Benefits & Perks
Esri’s competitive total rewards strategy includes industry-leading health and welfare benefits: medical, dental, vision, basic and supplemental life insurance for employees (and their families), 401(k) and profit-sharing programs, minimum accrual of 80 hours of vacation leave, twelve paid holidays throughout the calendar year, and opportunities for personal and professional growth. Base salary is one component of our total rewards strategy. Compensation decisions and the base range for this role take into account many factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.